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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 1-RES-JB
    11. 4867
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    Explanations

    words related to wells, especially in the context of monitoring and completion

    oai_token-act-pair · gpt-3.5-turbo

    references to water sources and monitoring

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    izophren
    -0.73
    IENCE
    -0.72
    RAW
    -0.71
    SHIP
    -0.66
     Hawth
    -0.66
     Pick
    -0.62
    IENT
    -0.62
    Rocket
    -0.62
     Junk
    -0.62
    shaw
    -0.62
    POSITIVE LOGITS
     wells
    1.20
     drilled
    0.96
    espie
    0.91
    esian
    0.85
     irrig
    0.83
    chool
    0.82
     groundwater
    0.82
     horizont
    0.80
    wine
    0.77
    lings
    0.77
    Activations Density 0.006%

    No Known Activations